Title

Learning unknown functions in cascaded nonlinear systems

Abstract

In this paper, tile problem of learning unknown time functions in cascaded nonlinear systems will be studied. The objective is to find an iterative learning control under which nonlinear systems are globally and asymptotically stabilized and the time functions contained in system dynamics are learned. By utilizing a new differential-difference learning law, a learning control is designed to yield both asymptotic stability of the state and asymptotic convergence of the learning error. The design is carried out by applying the backward recursive method.

Publication Date

12-1-1998

Publication Title

Proceedings of the IEEE Conference on Decision and Control

Volume

1

Number of Pages

165-169

Document Type

Article

Personal Identifier

scopus

Socpus ID

0032279950 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0032279950

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